Authorizations
Path Parameters
Project ID
Learn Block ID, use the impulse functions to retrieve the ID
Query Parameters
If set to "true", the "labels" field is left empty (which can be big on e.g. regression projects).
Response
OK
Whether the operation succeeded
Date when the model was trained
Layers of the neural network
Labels for the output layer
Original labels in the dataset when features were generated, e.g. used to render the feature explorer.
The types of model that are available
The model type that is recommended for use
int8
, float32
, akida
, requiresRetrain
Metrics for each of the available model types
classification
, regression
, object-detection
, visual-anomaly
, anomaly-gmm
Normalization that is applied to images. If this is not set then 0..1 is used. "0..1" gives you non-normalized pixels between 0 and 1. "-1..1" gives you non-normalized pixels between -1 and 1. "0..255" gives you non-normalized pixels between 0 and 255. "-128..127" gives you non-normalized pixels between -128 and 127. "torch" first scales pixels between 0 and 1, then applies normalization using the ImageNet dataset (same as torchvision.transforms.Normalize()
). "bgr-subtract-imagenet-mean" scales to 0..255, reorders pixels to BGR, and subtracts the ImageNet mean from each channel.
0..1
, -1..1
, -128..127
, 0..255
, torch
, bgr-subtract-imagenet-mean
List of configurable thresholds for this block.
Optional error description (set if 'success' was false)
mobilenet-ssd
, fomo
, yolov2-akida
, yolov5
, yolov5v5-drpai
, yolox
, yolov7
, yolo-pro
, tao-retinanet
, tao-ssd
, tao-yolov3
, tao-yolov4
, yolov11
, yolov11-abs
This is experimental and may change in the future.